Modelling three-dimensional directivity of sound scattering by Antarctic krill: progress towards biomass estimation using multibeam sonar

• Published in: ICES Journal of Marine Science
• Main Authors: Cutter, George R., Renfree, Josiah S., Cox, Martin J., Brierley, Andrew S., Demer, David A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press (OUP) 2009
• Subjects: Antarctic; Cape Shirreff; Livingston Island; Shirreff; Antarc*; Antarctic Krill; Antarctica; Euphausia superba
• Online Access: https://doi.org/10.1093/icesjms/fsp040; http://academic.oup.com/icesjms/article-pdf/66/6/1245/29133911/fsp040.pdf

Abstract Cutter, G. R., Renfree, J. S., Cox, M. J., Brierley, A. S., and Demer, D. A. 2009. Modelling three-dimensional directivity of sound scattering by Antarctic krill: progress towards biomass estimation using multibeam sonar. – ICES Journal of Marine Science, 66: 1245–1251. Target strength (TS) estimation is a principal source of uncertainty in acoustic surveys of Antarctic krill (Euphausia superba). Although TS is strongly dependent on krill orientation, there is a paucity of information in this regard. This paper considers the potential for narrow-bandwidth, multibeam-echosounder (MBE) data to be used for estimating the orientations of krill beneath survey vessels. First, software was developed to predict MBE measurements of the directivity patterns of acoustic scattering from individual or aggregated krill in any orientation. Based on the distorted-wave, Born approximation model (DWBA), scattering intensities are predicted vs. MBE angles for specified distributions of krill orientations (pitch, roll, and yaw angles) and swarm densities. Results indicate that certain distributions of orientations, perhaps indicative of particular behaviour, should be apparent from the sonar data. The model results are compared with measurements on krill made using a 200-kHz MBE deployed from a small craft off Cape Shirreff, Livingston Island, Antarctica, in summer 2006. The stochastic DWBA model is then invoked to explain disparities between the model predictions and MBE measurements.